In the past 15 years, we have seen that the dynamics of the exchange rate in Japan (JPY) has had a significant impact on equities; it has been described as a negative ‘Pavlovian’ relationship where a cheaper currency has usually been associated with higher equities. This chart shows the significant co-movement between Japanese equities – TOPIX – and the USDJPY exchange rate; hence, we are confident that policymakers in Japan are strongly aware of that relationship and therefore the BoJ is carefully and constantly watching the exchange rate.
It is interesting to see while the Japanese Yen has been constantly appreciating against the US Dollar amid the aggressive liquidity injections from the Fed (relative to BoJ), equities have strongly recovered from their March lows and are currently trading at their highest level since October 2018. However, we do not think that this relationship will persist in the medium term; as we previously mentioned, a strong Yen will not only dramatically impact the economic ‘recovery’ but also weigh on LT inflation expectations. The last time the relationship broke down between the two times series was in the beginning of 2018, with the TOPIX rising to nearly 1900 while the Yen was gradually strengthening against the USD, but it did not take long for equities to converge back to their ‘fair’ value.
We are not suggesting that trend in equities is about to revert, but investors should be careful as the ‘Short USD / Long The Rest’ trade has become very crowded.
Despite the 13% fall since March, investors’ sentiment on the USD is still extremely negative for 2021. We previously argued that central banks (ex-Fed) will not let the greenback depreciate indefinitely as it will dramatically impact the economic ‘recovery’ (i.e. Euro area is very sensitive to a strong exchange rate) and weigh on long-term inflation expectations. In addition, figure 1 shows that a weaker US Dollar has coincided with a positive momentum in equities in recent years, especially since the February/March panic; therefore, being long US Dollar at current levels could offer investors a hedge against a sudden reversal in risky assets in the short term.
Another interesting observation comes out when we look at the seasonality of the USD in the past 50 years; while December tends to be the worst month on average for the greenback, January has historically been the best performing month with the Dollar averaging nearly 1% in monthly returns since January 1971.
Is it time for a ST bull retracement on the US Dollar?
Even though some analysts have compared the 2020 rebound in equities to the 1930 ‘hope’ phase following the 1929 crash, we think that this year has shown some strong similarities with the 1998 / 1999 period. While tech stocks were experiencing strong inflows in the second half of the 1990s amid the dotcom boom, the Nasdaq suddenly fell by 30% in the third quarter of 1998, before starting to reach new highs and surging by over 120% in the following year.
This year, tech companies’ valuations are up 90% in the past 9 months following their dip reached on March 23rd and seem on their way to reach new all-time highs in the coming months as another 3 trillion USD is expected to reach markets in the coming year.
This chart shows some strong co-movements between the Nasdaq index in 1996 – 2000 and in August 2018 – December 2020. Even though market sentiment has reached extreme levels, the bullish trend in mega-cap growth stocks could easily continue for another year amid the surge in liquidity coming from central banks to support the economies and finance the high costs of lockdowns.
As we previously saw, the massive liquidity injection from major central banks to prevent the economies from falling into a global deflationary depression has generated a significant rebound in equities prices, especially for the mega-cap growth stocks. Figure 1 shows that the FANG+ index is trading over 50% higher than its February high, which was mainly driven by the surge in global liquidity.
In addition, the major 5 central banks (Fed, ECB, BoJ, PBoC and BoE) are expected to increase their balance sheet by another 5 trillion USD in the coming 2 years, to a total of 33 trillion USD, to cover the high costs of national lockdowns. As a result, ‘Wall Street’ strategists have constantly reviewed their SP500 forecasts for 2021 to the upside in recent months, with the average forecast rising to 4,035 in December according to Bloomberg.
With central banks ‘ready to act’ as soon as we see a sudden tightening in financial conditions (due to a drop in equities), the risk reward in the SP500 is currently skewed to the upside with all the liquidity injections expected to reach markets in the coming months.
Moving averages are the most widely used indicators in technical analysis, and help smoothing out short-term fluctuations (or volatility) in order to highlight a longer-term trend. Traders classically use the past daily (or intraday) prices to compute their time series, applying different variations of moving averages. In this article, we are going to look at a basic momentum strategy looking at a simple moving average (SMA) crossovers as our signal to buy or sell the underlying asset, gold. In this strategy, traders build a trading signal based on moving average crossovers, by taking a long position if the shorter (faster) moving average is above the longer (slower) moving average, and a short position if the shorter moving average is below the longer moving average (see more here).
For instance, the famous terms ’Golden Cross’ and ’Death Cross’ result from crossovers of the 50 SMA and the 200 SMA. ’Death Cross’ is when the 50 SMA crosses the 200 SMA to the downside, signalling a potential long-term bear market on gold (figure 1).
Which parameters should we use to build a SMA crossover strategy?
Even though the 50 and 200 SMAs are probably the most popular moving averages that investors tend to watch carefully, we first have to check if there have been different combinations in the past that have generated ‘enhanced’ returns. Therefore, using daily prices on gold, we look at different combinations of SMA crossovers, with the short SMA ranging from 2 to 50 and the long SMA ranging from 5 to 200. We then compute the Sharpe ratio of each of the combination, which we define as the ratio of the annualized returns over the annualized volatility of the entire sample:
As there are many different combinations, we decide to use a heatmap to detect if there are some ‘hot’ and ‘cold’ areas. How to read a heatmap is pretty straightforward:
The red areas are ‘hot’ areas, which implies that the SMA combinations have been working well in the past few years.
The green area are the ‘cold’ areas, which are the combination to avoid if you want to build a systematic strategy on gold using SMA crossovers.
In our first backtest, we look at the daily price of gold since 2016; results are shown in Heatmap 1A and 1B. It is important to know that the parameter of the short SMA cannot be bigger than the parameter of the long SMA (blue shaded area).
The ‘Death Cross’ strategy stands at the bottom right of the entire heatmap (Heatmap 1B) and has generated a Sharpe ratio of 0.75 over the past four years, which is less than the ‘long-only’ strategy (long GLD) with a Sharpe ratio of 0.87. The combination that has generated the highest performance is the (35,37) SMA crossovers, with a Sharpe ratio of 1.36.
Figure 2 (left frame) shows the equity curve of the long-only (GLD) versus the traditional ‘Death Cross’ and the (35,37) SMA crossovers. The (35,37) SMA crossover strategy shows that investors would have captured the late declining by going short GLD in the past few months. Figure 2 (right frame) shows the changes in signal for the two strategies; while the Death Cross strategy is very slow and has changed signals only 5 times in the past 5 years (currently sending a buying signal as 50D SMA is trading above the 200D SMA), the (35,37) has a higher frequency and has been sending a sell signal since mid-September to the exception of a few days. As we look at daily prices, we assume that the transaction costs are negligible for a commodity such as gold.
Heatmap 1. Sharpe ratios of SMA crossovers strategy using daily prices of gold since 2016
Heatmap 1A (Long SMA from 5 to 105)
Heatmap 1B (Long SMA from 105 to 200)
In our second backtest, we look at the daily price of gold since 2010 in order to capture the bearish momentum in gold prices that occurred in the first half of the last decade; results are shown in Heatmap 2A and 1B. First, we can notice that the Sharpe ratio are significantly lower, which is not surprising as gold consolidated sharply after reaching its previous high of in September 2011. The ‘Death Cross’ strategy has generated a Sharpe ratio of 0.29, which is again much lower than the ‘long-only’ strategy with a Sharpe ratio of 0.37.
The winner combination this is the (27,53) SMA crossover generating a Sharpe ratio of 0.64.
Figure 3 shows the equity curve of the long-only (GLD) versus the traditional ‘Death Cross’ and the (27,53) SMA crossovers. We can notice again that the Death Cross strategy have barely changed signals in the past decade.
Heatmap 2. Sharpe ratios of SMA crossovers strategy using daily prices of gold since 2010
Heatmap 2A (Long SMA from 5 to 105)
Heatmap 2B (Long SMA from 105 to 200)
Even though a lot of investors tend to focus significantly on the Death Cross 50/200 signal when defining bullish or bearish trends coming from momentum strategies, we have seen that this strategy has performed poorly in either the past 5 years or since 2010. We know that past performance does not guarantee future returns, but it is important to add the most powerful ‘quantitative tool’ to your fundamental analysis. At the moment, fundamentals signals on the GLD are mixed; on one hand, the weak USD and the large amount of negative-yielding debt are pricing in stronger GLD, but rising yields in the US could weigh on the pressure metal in the short run. As we saw in the article, the best combinations are also sending bearish signals on GLD.
Even though a significant amount of investors have become increasingly worried about the current state of the equity market and how ‘extremely stretched’ the equity positioning has been in recent weeks, they must not underestimate the force of the liquidity injections coming from central banks. Figure 1 shows the evolution of the major 5 central banks’ assets since 2002 (Fed, ECB, BoJ, PBoC and BoE); after rising by over 7 trillion USD since March, assets of the top 5 central banks are expected to grow by another USD 5tr in the coming two years up to USD 33tr in order to support the high costs of running restrictive economies to fight the pandemic.
Therefore, although some fundamental ratios such as price-to-sales or the traditional P/E ratio have reached stratospheric levels for some companies and also for the entire equity indexes (for instance, Robert Shiller’s CAPE ratio was of 33.1 in November, far above its 140-year average of 17.1), the constant liquidity injections could continue to support the equity market in the near to medium term, especially the FANG+ stocks. Figure 2 shows the strong co-movement between the total assets from the major 5 central banks and the FANG+ index; we can notice that the titanic rise in central banks assets has ‘perfectly’ matched the strong rebound in the mega-cap growth stocks in the past 8 months.
With 5 trillion USD of assets expected to be added in the coming 24 months, is it really time to be bearish on tech stocks? Figure 2
In the past few years, a significant amount of economists and practitioners have warned of a potential hard landing in the Australian housing market, as property prices have been growing at unsustainable rates with first-home buyers having difficulties saving a significant deposit to get a foothold in the market. According to the Australian Bureau of Statistics, the total value of residential property in Australia is now exceeding 7 trillion USD, by far the economy’s largest asset. As there are no ‘vehicles’ to short the Australian housing market as during the US subprime crisis, two alternative ways to short the property market was through either going short the Australian Dollar or short the banks. Prior the Covid19 crisis, banks’ mortgages were equivalent to approximately 80% of the country’ GDP, with most of them piled into the top 4 banks (Commonwealth, WestPac, ANZ and NAB).
Even though house prices were starting to decline significantly in 2018 and the beginning of 2019, with investors speculating that it was the start of the ‘hard landing’, the reversal in the global stance of monetary policy (from quantitative tightening to quantitative easing) combined with the surge in Chinese liquidity have generated strong support for the Australian property market in the past year. This chart shows an interesting co-movement between China excess liquidity (6M lead), which we compute as the difference between real M1 money growth and industrial production, and the Australian housing market. It seems that the downside risk in the Aussie property market should remain limited as money growth keeps accelerating in China.
With interest rates trading at or close to zero percent in most of the developed world, investors have been questioning if government bonds still act as a hedge against periods of market stresses, which are usually negative for equities. One of the most important characteristics of the traditional 60/40 equity bond (and also the ‘all-weather’ portfolio risk parity) has been the negative correlation between equity returns and changes in long-term bond yields. Figure 1 shows that the 3-rolling correlation between US equity returns and the 10Y bond yield turned negative in the beginning of 2000s after being positive for decades (using weekly times series)
However, we are not confident that the correlation will remain negative (implying that bonds are rising when equities are falling) in the medium term, especially if we switch to more inflationary environment after restrictions are lifted. Even though the disinflationary forces will remain significant in the coming 12 to 24 months due to social distancing, investors must not assign a zero-percent probability of a sudden rise in inflation expectations in the future.
Source: Eikon Reuter, RR calculations
Why not swap some of your bond allocation, which currently offers a very limited upside, for gold, which offers ‘unlimited’ upside gains as money supply continues to grow dramatically in most of the economies. Figure 2 shows the performances (and drawdowns) of four different portfolios:
A equity long-only portfolio
A 60/40 equity bond portfolio
A 60/35/5 equity bond gold portfolio
A 60/30/10 equity bond gold portfolio
We can notice that investors would have got similar returns if they had held 5 to 10 percent of gold in their portfolio instead of bonds in the past 50 years. It is time to diversify the traditional 60/40 equity bond portfolio.
Unlike bonds or equities, currencies do not carry any fundamental value and have historically been known as the most difficult market to predict. In our FX fair value model page, we look at different ways of estimating a ‘fair’ value for a bilateral exchange rate. One of the simplest models is based on the Purchasing Power Parity theory, which stipulates that in the long run, two currencies are in equilibrium when a basket of goods is priced the same in both countries, taking the account the exchange rates. We know that the OECD publishes the yearly ‘fair’ exchange rate based on the PPP theory or each economy.
Based on the OECD calculations, it appears that the Euro is the most undervalued currency among the G10 world relative to the US Dollar, as PPP prices in a fair rate of 1.42 (implying that EURUSD is 18% undervalued). On the other hand, the Swiss Franc is the most undervalued currency (+26%). Therefore, if we were to believe that exchange rates converge back to their ‘fundamental’ value in the long run, being long EURCHF is the position with the most interesting risk premia among the DM FX world.
In the past cycle, central banks have been constantly intervening in the market to counter the strong disinflationary force coming from the 3D: Debt, Demographics, Disruption. Figure 1 shows that between the beginning of 2008 and early 2020, the assets from the major 5 central banks grew steadily by a annual pace of $1.25tr per year, for a total of $15tr in 12 years.
As a response to the Covid19 shock, central banks just printed more in order to prevent the economies from falling into a deflationary depression, which resulted in a 7-trillion-dollar increase in central banks’ assets in the past 8 months. The titanic liquidity injections resulted in a significant rebound in equities, especially in the US with the SP500 trading over 100 points above its February high.
With most of the European economies entering a second lockdown, and restrictions also expected to be announced in the US (as the elections are now over), governments will again run aggressive fiscal policies and extend the furlough schemes in order to avoid the rise of social unrest, which will result in more money printing from central banks in the coming months.
Is it as simple as this: the worst the economy gets, the better it is for stocks as it will result in more liquidity injections?